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Connectivity Versus Entropy

Abu-Mostafa, Yaser S. (1988) Connectivity Versus Entropy. In: Neural Information Processing Systems. American Institute of Physics , New York, NY, pp. 1-8. ISBN 0883185695. http://resolver.caltech.edu/CaltechAUTHORS:20160107-155110636

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Abstract

How does the connectivity of a neural network (number of synapses per neuron) relate to the complexity of the problems it can handle (measured by the entropy)? Switching theory would suggest no relation at all, since all Boolean functions can be implemented using a circuit with very low connectivity (e.g., using two-input NAND gates). However, for a network that learns a problem from examples using a local learning rule, we prove that the entropy of the problem becomes a lower bound for the connectivity of the network.


Item Type:Book Section
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Additional Information:© 1988 AIP.
Record Number:CaltechAUTHORS:20160107-155110636
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160107-155110636
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:63467
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:19 Jan 2016 22:59
Last Modified:19 Jan 2016 22:59

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